Using Machine Learning Models to Evaluate the Performance of Website in Iraqi Universities

Abstract

Academic website played a main role in giving information about academic institutions and view the services that introduced to their users. The purpose of this research evaluates the performance of Iraqi universities websites. A dynamic regression model was built. Created a dataset with 113 university websites then preprocessed executed at first then apply a correlation statistics method for determine the most features that influenced at the prediction of performance. Lastly, eight machine learning regression models was applied. After that compared these models, SGD regressor give the best result of evaluation metrics from other models were applied. For increasing the quality of a websites performance, academic institutions should take the result obtained from this research.